numpy.ma.MaskedArray.reshape
method
-
MaskedArray.reshape(self, *s, **kwargs)
[source] -
Give a new shape to the array without changing its data.
Returns a masked array containing the same data, but with a new shape. The result is a view on the original array; if this is not possible, a ValueError is raised.
- Parameters
-
-
shapeint or tuple of ints
-
The new shape should be compatible with the original shape. If an integer is supplied, then the result will be a 1-D array of that length.
-
order{‘C’, ‘F’}, optional
-
Determines whether the array data should be viewed as in C (row-major) or FORTRAN (column-major) order.
-
- Returns
-
-
reshaped_arrayarray
-
A new view on the array.
-
See also
-
reshape
-
Equivalent function in the masked array module.
-
numpy.ndarray.reshape
-
Equivalent method on ndarray object.
-
numpy.reshape
-
Equivalent function in the NumPy module.
Notes
The reshaping operation cannot guarantee that a copy will not be made, to modify the shape in place, use
a.shape = s
Examples
>>> x = np.ma.array([[1,2],[3,4]], mask=[1,0,0,1]) >>> x masked_array( data=[[--, 2], [3, --]], mask=[[ True, False], [False, True]], fill_value=999999) >>> x = x.reshape((4,1)) >>> x masked_array( data=[[--], [2], [3], [--]], mask=[[ True], [False], [False], [ True]], fill_value=999999)
© 2005–2020 NumPy Developers
Licensed under the 3-clause BSD License.
https://numpy.org/doc/1.19/reference/generated/numpy.ma.MaskedArray.reshape.html